Questions tagged [forecasting]

Prediction of the future events. It is a special case of [prediction], in the context of [time-series].

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18 views

Cyclicality in time series

The high amount of cyclicality in the lynx time series makes it very difficult to model with ets and ...
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14 views

Forecasting a binary time series [duplicate]

My (real) problem is as follows: I have a weekly time series about orders of a given product in a specific bar. Let's say that we have a 0 when the bar doesn't order in that week and 1 when it does. ...
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8 views

estimate “et” error terms / residuals of SARIMA from equation

I want to estimate manually (from equation/algorithm) the predicted values of the model "(2,1,0) (0,0,2) [7]". However, the equation estimates the fitted values. I want to know how estimate "et" to ...
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11 views

Is applying an ARMA model to a stationary series the same as applying it to a trend and seasonally adjusted series?

Is it true that regular differencing and seasonal differencing of a time-series to achieve stationarity, is the same thing as adjusting a time-series for trend and seasonality? If the above statement ...
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KPSS test thinks that regression is spurious

It should be obvious that there is a relationship between the market price of black pepper and the market price of white pepper. ...
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13 views

Detecting spurious regression by testing the residuals

A linear regression between "Number of Australian Air Passengers" and "Rice Production in Guinea" reveals a "strong" but probably spurious relationship between the two time series. ...
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13 views

Is Box-Jenkins approach to time-series prediction and forecasting similar to Unobserved Components models approach?

How I understand the Box-Jenkins Method in a nut-shell is that a time-series model has signals that can be identified by weighting its own past lagged values, or weighting its owned past errors or ...
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33 views

Incorporate additional information in Stock Forecasting

I am trying to forecast stock of health products. Other than historical stock quantity, I would have some other information, e.g.,: Certain stocks are in compete of each other; Certain stocks are ...
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35 views

Is time series analysis suitable for long term predicting/forecasting?

Can I use time series analysis to predict/forecast long term ? Example using ARIMA, how can I explain the back of the theory its?
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Estimate the time series like an event was never happened

I have data from a website where a specific advertising campaign happened a couple of years ago. What I want to do is to estimate how the signups on that website would have been without that big ...
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19 views

ARIMA(0, 1, 0) or ARIMA(0, 0, 0) for Stock log-Returns Forecast

I'm trying to forecast the log-returns of Amazon's stocks using the ARIMA model, so I went through the traditional procedure of examining the autocorrelation plot and the partial autocorrelation plot ...
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If prediction intervals become narrower when less historical data is provided, how do you justify using a full range of data?

In forecasting (ets) annual data, I notice that when I use the full data set of 10 years, the prediction intervals are much wider than when using an abridged version of the data set (5 years). I ...
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How to find FFT for a window period of a given large time series data?

If i binned time series data for particular time interval 't' and choose a window period of lets say 5 bins and converted into n rows as train data(5 bins for each row) and a y_value(need to be ...
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20 views

Diebold Mariano test Nested Models

I have computed forecasts with 4 different methods, namely OLS, Elastic Net, Cubic splines in combination with Lasso, and Neural Network. All models use the same set of base variables, except cubic ...
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How do I forecast quarterly public expenses based on annual budgets and potentially other variables?

I have some time series data from 2008 and forward (see below) on quarterly public expenses and annual public budgets. I would like to forecast the last two quarters of 2018 as precisely as possible, ...
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Significance of hyper parameters in the DHR model in R forecast package

The Dynamic Harmonic Regression model in R requires the input of parameters K, the length of which depends on the number of seasonality in the forecast data. According to https://otexts.com/fpp2/dhr....
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94 views

Neural Network regression on time series

I want to predict the trend values of a time serie [Y] based on the effect of other 10 input variables which can also have interaction. Since the combination of interaction between the inputs is ...
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1answer
23 views

ARIMA Time Series Simulation - Media Mix Model

I have designed and tested a time series model where I am able to examine the impact of various marketing channels on dependent variables (Such as sales, revenue, website traffic, etc). The model has ...
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Dont we accept the hypotheise of efficent market ıf we use ARIMA model to forecast or predict? [closed]

I estimate ARIMA models or another models that explain now price with past pirce. If I use this models , already ı reject efficient market hypothesis? I write master thesis and my teacher asked me ...
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R forecast script - how to ignore current month in the calculation? [migrated]

I am using the following R script (in Tableau) to do monthly forecast, using package "forecast". It works without errors but I would like to exclude current month from the calculations. ...
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Is it possible to to compare ARIMA and ARMA-GARCH model with different series?

I have some questions with model compares ion and forecasting. The row data (quarterly traffic accident numbers) is not stationary but it is stationary at first difference. we can model and forecast ...
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HAR model estimation in R studio [closed]

After splitting my data as the "in and out-of-sample" for volatility forecasting purpose in R, I estimate HAR model, but my estimated HAR model is for the whole sample. It does not estimate for the in ...
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1answer
38 views

Can I give continuous rank probability score (CRPS) to Diebold-Mariano (DM) test?

I would like to use DM test for probabilistic forecasting case. My initial thinking was to give CRPS of two forecasting methods instead of raw forecast errors, where CRPS is calculated using ...
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Why BSTS model gives very different forecasts depending on length of testing set?

When I run a BSTS model in R, I get a finished model from a data set, and when I use that model to predict, for example, like this: predict(model3,newdata=futuredata) -> pred_1 I get a set of ...
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1answer
37 views

Sarima : Fitting on train subset works but fitting on whole train does not [closed]

I use SARIMAX from statsmodels.tsa.statespace.sarimax in Python. I have a simple one column energy consumption dataset with 27679 rows. The frequency is Hour. I do hyperparameters optimization ...
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How is the method of Eviews dynamic forecasting? [closed]

One [answer]1 says that dynamic forecast use forecasted value instead of actual value.Yes it is logical. But other answer says dynamic forecast use n step ahead.Example if you want to 10 days or 100 ...
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53 views

Is ARIMAx a transfer function model?

I would like to know if the ARIMAx model is considered a transfer function model. If the answer is no, further explanation on what are differences would be appreciated.
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Future event prediction methodology

I have a data set such that each data point is an "event" with features $x_1, x_2, \dots, x_n$ and the year of its occurence $y$. I want to train a forecasting model that predicts when an event of ...
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1answer
30 views

Manually adjusting forecasting model bias

I am trying to build an efficient forecasting model to predict sales in the future. I managed to obtain a first pretty solid model using a LSTM network. However, it wasn't sensible enough to large ...
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How to plot the ARIMA fitted values of a time series in R?

I'm currently analyzing the stock market price indices for my undergrad research. Namely, ASPI: all share price index(abbrv:aspi) & SL S&P 20 (abbrv :std) auto.arima() gives me the following ...
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Forecasting daily data with zeros in Python

I'm currently testing some forecasts on daily sales quantities. However, out of ~2000 observations I have 16 zeros. How should I approach this? It's mainly Sundays and holidays that holds zero as ...
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1answer
21 views

Time series forecasting: How can I adjust my forecast to incorporate external predictions at a different time scale?

I have information about past and future values that I want to incorporate into my timeseries model (experimenting with ARIMA and other models) in order to predict the future at a more granular ...
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2answers
83 views

Incorporating Prior Information Into Time Series Prediction

Suppose I have data on my child C's height measured every week. Presumably there is a positive trend, due to growth, and some noise due to measurement errors, and maybe even seasonality (winter boots ...
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Forecasting time series for categorical variables

I have time-series data with daily sales for shops and sold items. I would like to predict the number of each product sold in each store. What is the best way to solve this problem? It is necessary to ...
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11 views

Treating seasonality in Partial Least Squares forecast

I've been looking for answers on this question but couldn't find concrete solutions so wanted to ask y'all. I have been playing around trying to forecast an economic/financial-related indicator with ...
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1answer
37 views

Time series Data : Regress absolute values or regress the %growth of the values?

I am doing a time-series data analysis. The idea is to produce a forecast from the regression output. I am regressing Air traffic passengers of country A with GDP/capita of country A. I am getting ...
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time series forecasting - ljung-box test - degrees of freedom to subtract when working with breaks

I'm working on a differentiated seasonal time series with 2 breaks and non-zero mean. So, besides the constant i've got 2 dummies for breaks correction. Question: when performing LB test, if my model ...
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12 views

Vector Time Series: Capturing Systematic and Nonsystematic Patterns in Multiple Datasets | Financial Option Data

How does time series work with multiple time series data sets on the same index? For example, suppose I were a utilities company. Suppose I have the electricity usage of two homes, each indexed for ...
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109 views

Estimating prediction interval of ARMA process using R forecast function

the theme is forecasting with ARMA models. I'm trying to understand how the R forecast function works if applied to an ...
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2answers
85 views

Forecasting in a state-space model from a Bayesian perspective

We have the following state-space model(or linear dynamical model): \begin{align} x_t&\sim N(Ax_{t-1},Q)\\ y_t&\sim N(Bx_{t},\Sigma) \end{align} I want to obtain a sample from $p(y_{T+1}\mid ...
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How to use forecast data in neural net when forecast produced periodically?

I am considering how to structure a neural net problem where an input forecast (say, for chocolate production) is produced for 'k' time periods. This forecast is produced every time period. and I ...
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2answers
78 views

Is my Data stationary? KPSS, ADF Tests and ACF

I already differenced my Data by 1 and i am not sure whether my Data is now stationary or not. I perfomed an KPSS and ADF test in order to help me decide if it is. I think it is stationary but im not ...
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ARMA Forecasting - Professional Work

I was curious how long does it take you to do ARMA forecasts in your professional environments? I'm getting started using the "Real Statistics" Add-On in Excel & I have only been familiar with ...
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2answers
38 views

How are missing data handled in Time series estimation?

I am looking for most popular/theoretically sound methods for handling missing data in time series model (particularly ARMA class) estimation. Also what method is used in R (in arima and in forecast ...
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2answers
104 views

Multi-step ahead forecasting with LSTM neural network

I would like to forecast the heat load of a district heating network given its past values, the temperature and the 3-day ahead forecast of the temperature with an LSTM RNN. The data is hourly and I ...
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1answer
81 views

Forecasting recurring orders for an online subscription business using Facebook Prophet and R

I am analyzing data from a subscription model, in which a customer must pay a recurring price at a regular interval (30 days) for access to the product. EDIT -> Direct link to daily data: https://...
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How do you evaluate bias and/or quality of time-series forecasts

I am working on a financial model that will forecast the revenue a company generates over a fiscal quarter, and I am not sure of the best way to rigorously evaluate the bias in the model. Every day ...
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1answer
37 views

Modeling non-linear (short) time series and cross-validate them

beginner data scientist here. Time series analysis is a completly new area for me, so please correct me if i write something that makes no sense. I have many multivariante short time series, between ...
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2answers
115 views

Predicting walking routes using PyTorch

I'm working on a project that uses sensors to monitor a persons location. These devices simply record the current GPS coordinates and ping them back to a server (the coordinates will then be converted ...
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how to calculate safety stock from output of ARIMA model?

I have built an arima model using monthly sales as input suppose the output from ARIMA model is : How do we calculate safety stock for different lead times lead times (in days)?? ...